TRACKING BACTERIA AND FUNGI DIVERSITY FROM NATURAL WATER SOURCES TO DRINKING WATER TREATMENT PLANTS AND DISTRIBUTION SYSTEMS - A REVIEW

被引:1
作者
Mudau, K. L. [1 ]
Kalu, C. M. [1 ]
Masindi, V. [1 ,2 ]
Maphangwa, K. W. [1 ]
Tekere, M. [1 ]
机构
[1] Univ South Africa, Coll Agr & Environm Sci, Dept Environm Sci, ZA-1710 Florida, South Africa
[2] Sci Serv, Res & Dev Div, Magalies Water, Brits, South Africa
来源
APPLIED ECOLOGY AND ENVIRONMENTAL RESEARCH | 2024年 / 22卷 / 01期
关键词
artificial intelligence; membrane technology; anthropogenic activities; coagulation-flocculation; disinfection stage; ANTIBIOTIC-RESISTANCE GENES; ARTIFICIAL NEURAL-NETWORKS; DISINFECTION BY-PRODUCTS; MICROBIAL COMMUNITIES; BIOFILM FORMATION; ORGANIC-MATTER; SURFACE-WATER; HEXAVALENT CHROMIUM; FILAMENTOUS FUNGI; SUPPLY SYSTEM;
D O I
10.15666/aeer/2201_507537
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
The complete removal of bacterial and fungal communities found in natural water sources by drinking water treatment plants (DWTPs) is a global issue of concern as many of these microbes are passed down to the end users through the drinking water distribution systems (DWDSs). An overview of the bacterial and fungal communities present in natural water sources is provided. The abundance of the bacterial and fungal communities in the final water exiting DWTPs and tap water from DWDSs provides an insight into the treatment plants' effectiveness. Information on the different technologies including artificial intelligence (AI) used in the water treatment plants was collated to elucidate their role in drinking water treatment. Based on previous studies, Proteobacteria, Firmicutes, Nitrospirae, and Actinobacteria are the predominant bacterial phyla while Aspergillus, Cladosporium and Penicillium, Fusarium and Trichoderma are the predominant fungal phyla identified in the final water and tap water. Information on the performance of advanced treatment shows the positive impact of the technology in bacteria and fungi removal. Furthermore, the application of AI in water treatment for the determination of coagulant dosages and prediction of the disinfectant is also promising. Research gaps were identified, and future studies were recommended to address water treatment concerns.
引用
收藏
页码:507 / 537
页数:31
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